Field of the Invention
The present invention relates to an image processing technique of processing a medical image.
Description of the Related Art
In recent years, the quality of medical images captured by three-dimensional imaging apparatuses such as a radiation computer tomography apparatus (radiation CT) and a nuclear magnetic resonance imaging apparatus (MRI) has dramatically improved, and it is therefore possible to obtain microscopic internal information of a human body. Accordingly, however, as the number of images increases, the burden on a radiologist in diagnostic interpretation increases every year, and expectations are increasingly running high for diagnosis support (Computer Aided Diagnosis: CAD). In diagnosis support for benign/malignant discrimination, therapeutic effect confirmation, or the like, it is important to estimate the shape of a target such as a tumor.
Concerning target shape estimation, for example, each of non-patent literatures 1 and 2 discloses a technique for estimating the shape of a pulmonary nodule that exhibits a convex mass as a region having a higher intensity value than in the periphery from a chest CT image using the scale space of a filter.
In non-patent literature 1 (S. Diciotti, et al., The LoG Characteristic Scale: A Consistent Measurement of Lung Nodule Size in CT Imaging. IEEE Trans. Med. Imag., Vol. 29(2), pp. 397-409, 2010), when applying a Laplacian of Gaussian (LoG) filter to a target in different scales (values of a function with respect to Gaussian σ), the local maximum of output values is obtained near the center point of the target. A scale corresponding to the obtained local maximum is selected as a parameter representing the shape of a pulmonary nodule (the diameter of an approximate sphere). Non-patent literature 2 (K. Okada: Ground-Glass Nodule Characterization in High-Resolution CT Scans. In Lung Imaging and Computer Aided Diagnosis. Taylor and Francis, LLC, 2011) discloses a technique of applying a Gaussian filter to a target in different scales and selecting most appropriate σ from the output values. Also disclosed is calculating the eigenvalue of σ using eigenvalue decomposition as a parameter representing the shape of a pulmonary nodule (approximate ellipse).
In a CT image, an isolated tumor region often exhibits a convex mass. However, there also exists a tumor region exhibiting a concave mass having a lower intensity value than in the periphery depending on the type of lesion or a cause such as contact with a neighboring organ. Also there exists a region including both a convex region and a concave region because of calcification, cavity, or the like. In the techniques of non-patent literatures 1 and 2, the shape is estimated assuming that the intensity distribution attribute of the target is known. For this reason, if the intensity distribution attribute of the target is not grasped in advance, it may be difficult to accurately obtain the outer shape of the target.
The present invention provides an image processing technique capable of accurately obtaining the shape of a target independently of the shape, texture, and relationship to a neighboring object.